pandas Sklearn逻辑回归，绘制概率曲线图
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Sklearn logistic regression, plotting probability curve graph
提问by Tony
I'm trying to create a logistic regression similar to the ISLR's example, but using python instead
我正在尝试创建一个类似于 ISLR 示例的逻辑回归，但使用 python
data=pd.read_csv("data/Default.csv")
#first we'll have to convert the strings "No" and "Yes" to numeric values
data.loc[data["default"]=="No", "default"]=0
data.loc[data["default"]=="Yes", "default"]=1
X = data["balance"].values.reshape(-1,1)
Y = data["default"].values.reshape(-1,1)
LogR = LogisticRegression()
LogR.fit(X,np.ravel(Y.astype(int)))
#matplotlib scatter funcion w/ logistic regression
plt.scatter(X,Y)
plt.xlabel("Credit Balance")
plt.ylabel("Probability of Default")
But I keep getting the graph on the left, when I want the one on the right:
但是当我想要右边的图时，我一直在左边的图：
Edit: plt.scatter(x,LogR.predict(x))was my second, and also wrong guess.
编辑：plt.scatter(x,LogR.predict(x))是我的第二个，也是错误的猜测。
采纳答案by chrisckwong821
you use predict(X)which gives out the prediction of the class.
replace predict(X)with predict_proba(X)[:,1]which would gives out the probability of which the data belong to class 1.
你使用predict(X)它给出了类的预测。替换predict(X)为predict_proba(X)[:,1]which 将给出数据属于第 1 类的概率。
回答by Woody Pride
You can use seaborn regplotwith the following syntax
您可以使用具有以下语法的seaborn regplot
import seaborn as sns
sns.regplot(x='balance', y='default', data=data, logistic=True)
